Ambiguity & Prosody The Influence of Prosody and Ambiguity on English Relativization Strategies Ted Briscoe & Paula Buttery Computer Laboratory and RCEAL University of Cambridge Interdisciplinary Approaches to Relative Clauses, Sept07
Ambiguity & Prosody Complexity and Ambiguity SRCs vs. NSRCs The guy who/that likes me just smiled The guy who/that/0 I like e just smiled Complexity: Distance between ‘filler’ and ‘gap’ Unbounded dependencies potentially complex
Ambiguity & Prosody Complexity and Ambiguity SRCs vs. NSRCs The guy who/that likes me just smiled The guy who/that/0 I like e just smiled Complexity: Distance between ‘filler’ and ‘gap’ Unbounded dependencies potentially complex
Ambiguity & Prosody Complexity and Ambiguity SRCs vs. NSRCs The guy who/that likes me just smiled The guy who/that/0 I like e just smiled Complexity: Distance between ‘filler’ and ‘gap’ Unbounded dependencies potentially complex
Ambiguity & Prosody Complexity and Ambiguity SRCs vs. NSRCs The guy who/that likes me just smiled The guy who/that/0 I like e just smiled Complexity: Distance between ‘filler’ and ‘gap’ Unbounded dependencies potentially complex
Ambiguity & Prosody Complexity and Ambiguity NSRCs and Ambiguity The guy who I think you want e? to succeed e? just smiled The guy who I want e? to think that the boss will succeed e? succeed = win / replace, intrans / trans Ambiguity: Distance between filler and potential gap, and potential gap and actual gap Unbounded ambiguities potentially complex
Ambiguity & Prosody Complexity and Ambiguity NSRCs and Ambiguity The guy who I think you want e? to succeed e? just smiled The guy who I want e? to think that the boss will succeed e? succeed = win / replace, intrans / trans Ambiguity: Distance between filler and potential gap, and potential gap and actual gap Unbounded ambiguities potentially complex
Ambiguity & Prosody Complexity and Ambiguity NSRCs and Ambiguity The guy who I think you want e? to succeed e? just smiled The guy who I want e? to think that the boss will succeed e? succeed = win / replace, intrans / trans Ambiguity: Distance between filler and potential gap, and potential gap and actual gap Unbounded ambiguities potentially complex
Ambiguity & Prosody Complexity and Ambiguity NSRCs and Ambiguity The guy who I think you want e? to succeed e? just smiled The guy who I want e? to think that the boss will succeed e? succeed = win / replace, intrans / trans Ambiguity: Distance between filler and potential gap, and potential gap and actual gap Unbounded ambiguities potentially complex
Ambiguity & Prosody Evolutionary Linguistics Universal Darwinism 1 Linguistic Variation + 2 Language Acquisition + 3 Linguistic Selection = 4 Linguistic Evolution
Ambiguity & Prosody Evolutionary Linguistics Universal Darwinism 1 Linguistic Variation + 2 Language Acquisition + 3 Linguistic Selection = 4 Linguistic Evolution
Ambiguity & Prosody Evolutionary Linguistics Universal Darwinism 1 Linguistic Variation + 2 Language Acquisition + 3 Linguistic Selection = 4 Linguistic Evolution
Ambiguity & Prosody Evolutionary Linguistics Universal Darwinism 1 Linguistic Variation + 2 Language Acquisition + 3 Linguistic Selection = 4 Linguistic Evolution
Ambiguity & Prosody Evolutionary Linguistics Linguistic Selection 1 Learnability – frequency, interpretability, learning bias... 2 Expressiveness – economy of production, memorability, prestige... 3 Interpretability – ease of perception, resolution of ambiguity...
Ambiguity & Prosody Evolutionary Linguistics Linguistic Selection 1 Learnability – frequency, interpretability, learning bias... 2 Expressiveness – economy of production, memorability, prestige... 3 Interpretability – ease of perception, resolution of ambiguity...
Ambiguity & Prosody Evolutionary Linguistics Linguistic Selection 1 Learnability – frequency, interpretability, learning bias... 2 Expressiveness – economy of production, memorability, prestige... 3 Interpretability – ease of perception, resolution of ambiguity...
Ambiguity & Prosody The Model A Lexicon Fragment who(m) (N \ N)/(S/NP) I S/(S \ NP) want ((S \ NP)/NP)/VP (S \ NP)/VP succeed (S \ NP)/NP S \ NP . . .
Ambiguity & Prosody The Model Combinatory Categorial Grammar Forward Application (FA): X/Y Y ⇒ X λ y [X(y)] (y) ⇒ X(y) Backward Application (BA): Y X \ Y ⇒ X λ y [X(y)] (y) ⇒ X(y ) Forward Composition (FC): X/Y Y/Z ⇒ X/Z λ y [X(y)] λ z [Y(z)] ⇒ λ z [X(Y(z))]
Ambiguity & Prosody The Model A Derivation who I want to succeed (N \ N)/(S/NP) S/(S \ NP) ((S \ NP)/NP)/VP VP/(S \ NP) S \ NP ------------------- FC (S/NP)/VP ---------------------- FC ((N \ N)/S)/VP ------------ FA VP ------------------------------------------ FA (N \ N)/S . . . who I want e to succeed
Ambiguity & Prosody The Model Parsability Stack Cells Lookahead Input Buffer 2 1 (who) (you want) to succeed (N \ N)/(S/NP) (S/NP)/VP VP/(S \ NP) S/VP Costs / cell 4 2 3 Shifts, 1 Reduce to reach this configuration Onset of the shift-reduce ambiguity at the first potential gap
Ambiguity & Prosody The Model Working Memory Cost Metric After each parse step (Shift, Reduce, Halt): 1 Assign any new Stack entry in the top cell (introduced by Shift or Reduce) a cost of 1 multiplied by the number of CCG categories for the constituent represented (Recency) 2 Increment every Stack cell’s cost by 1 multiplied by the number of CCG categories for the constituent represented (Decay) 3 Push the sum of the current costs of each Stack cell onto the Cost-record (complexity at each step, sum = tot. Complexity)
Ambiguity & Prosody The Model Optimal Ambiguity Resolution Default Parsing Preference: Prefer Shift over Reduce when Lookahead item can be integrated with cell 1 by Reduce Predicts preference for more costly late gap analysis (contra Gibson, 1998) This is the optimal strategy if the extrasyntactic information required to override the default action is available at the onset of the ambiguity Other things being equal, we expect languages and usage to evolve via linguistic selection for Interpretability using the optimal strategy
Ambiguity & Prosody The Model Optimal Ambiguity Resolution Default Parsing Preference: Prefer Shift over Reduce when Lookahead item can be integrated with cell 1 by Reduce Predicts preference for more costly late gap analysis (contra Gibson, 1998) This is the optimal strategy if the extrasyntactic information required to override the default action is available at the onset of the ambiguity Other things being equal, we expect languages and usage to evolve via linguistic selection for Interpretability using the optimal strategy
Ambiguity & Prosody The Model Optimal Ambiguity Resolution Default Parsing Preference: Prefer Shift over Reduce when Lookahead item can be integrated with cell 1 by Reduce Predicts preference for more costly late gap analysis (contra Gibson, 1998) This is the optimal strategy if the extrasyntactic information required to override the default action is available at the onset of the ambiguity Other things being equal, we expect languages and usage to evolve via linguistic selection for Interpretability using the optimal strategy
Ambiguity & Prosody The Model Optimal Ambiguity Resolution Default Parsing Preference: Prefer Shift over Reduce when Lookahead item can be integrated with cell 1 by Reduce Predicts preference for more costly late gap analysis (contra Gibson, 1998) This is the optimal strategy if the extrasyntactic information required to override the default action is available at the onset of the ambiguity Other things being equal, we expect languages and usage to evolve via linguistic selection for Interpretability using the optimal strategy
Ambiguity & Prosody Psycholinguistic Data Structural vs. Lexical Preferences The guy who you wanted to give the present to Sue refused The guy who you asked to give the present to Sue refused P((S \ NP)/VP | want) >> P(((S \ NP)/NP)/VP | want) P((S \ NP)/VP | ask) << P(((S \ NP)/NP)/VP | ask
Ambiguity & Prosody Psycholinguistic Data Structural vs. Lexical Preferences The guy who you wanted to give the present to Sue refused The guy who you asked to give the present to Sue refused P((S \ NP)/VP | want) >> P(((S \ NP)/NP)/VP | want) P((S \ NP)/VP | ask) << P(((S \ NP)/NP)/VP | ask
Ambiguity & Prosody Psycholinguistic Data Structural vs. Lexical Preferences The guy who you wanted to give the present to Sue refused The guy who you asked to give the present to Sue refused P((S \ NP)/VP | want) >> P(((S \ NP)/NP)/VP | want) P((S \ NP)/VP | ask) << P(((S \ NP)/NP)/VP | ask
Ambiguity & Prosody Psycholinguistic Data Structural vs. Lexical Preferences The guy who you wanted to give the present to Sue refused The guy who you asked to give the present to Sue refused P((S \ NP)/VP | want) >> P(((S \ NP)/NP)/VP | want) P((S \ NP)/VP | ask) << P(((S \ NP)/NP)/VP | ask
Recommend
More recommend
